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Record W2027820023 · doi:10.1145/1054972.1055013

Comparing cursor orientations for mouse, pointer, and pen interaction

2005· article· en· W2027820023 on OpenAlexafffund
Barry A. Po, Brian Fisher, Kellogg S. Booth

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPointer (user interface)Cursor (databases)Computer scienceInteraction techniqueTouchpadPointing device3D interactionHuman–computer interactionComputer graphics (images)Input deviceComputer visionGestureVirtual realityComputer hardware

Abstract

fetched live from OpenAlex

Most graphical user interfaces provide visual cursors to facilitate interaction with input devices such as mice, pointers, and pens. These cursors often include directional cues that could influence the stimulus-response compatibility of user input. We conducted a controlled evaluation of four cursor orientations and an orientation-neutral cursor in a circular menu selection task. Mouse interaction on a desktop, pointer (i.e. wand) interaction on a large screen, and pen interaction on a Tablet PC were evaluated. Our results suggest that choosing appropriate cursors is especially important for pointer interaction, but may be less important for mice or pens. Cursors oriented toward the lower-right corner of a display yielded the poorest performance overall while orientation-neutral cursors were generally the best. Advantages were found for orientations aligned with the direction of movement. We discuss these results and suggest guidelines for the appropriate use of cursors in various input and display configurations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.860
Threshold uncertainty score0.251

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.315
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations29
Published2005
Admission routes2
Has abstractyes

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